Group of analysis and validation of experiments- evaluation of the implementation of features through Causal Inference - analyzing of time series, model building and cross-validation, SEO-tests- search for causal relationships using ML: clustering, regression- development of dashboards for AB platform quality control- validation of AB tests and metrics in the company, consulting analysts

Group of analysis and validation of experiments- performed a study on CUPED for further rollout to the AB platform (verification of implementations, selection of covariate periods, reduction of MDE for ratio-metrics)- checked more than 300 A/B test designs before launching them: code-review (optional help for analysts) MDE calculation for Fixed Horizon experiments, Sequential testing, stratification, CUPED, linearization, application of statistical criteria for different types of metrics).- verified the performance of the new hash function in splitting, evaluated SRM on past tests- post-validation: analyzing the results of A/B tests, increasing the sensitivity of metrics- development and validation of metrics aggregates, adding them to the A/B platform (SQL, Python, GitLab)- ad-hoc analytics, customization of ETL processes